Synchronous Generator

Synchronous generators (SGs) are a core component of power systems, and research focuses on improving their modeling and control, particularly in the context of integrating renewable energy sources. Current research employs various machine learning techniques, including recurrent neural networks (RNNs) and deep operator networks (DeepONets), to learn SG dynamics and predict their behavior under diverse conditions, often leveraging data from electromagnetic transient (EMT) simulations. This work is crucial for enhancing power grid stability, reliability, and efficiency, enabling more effective integration of renewable energy and improved fault diagnosis and prediction.